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https://github.com/modelscope/FunASR
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cer
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游雁
parent
1ef8117213
commit
ad99b15120
@ -2,178 +2,189 @@ import os
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import numpy as np
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import sys
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import hydra
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from omegaconf import DictConfig, OmegaConf, ListConfig
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def compute_wer(ref_file,
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hyp_file,
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cer_file,
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cn_postprocess=False,
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):
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rst = {
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'Wrd': 0,
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'Corr': 0,
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'Ins': 0,
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'Del': 0,
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'Sub': 0,
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'Snt': 0,
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'Err': 0.0,
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'S.Err': 0.0,
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'wrong_words': 0,
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'wrong_sentences': 0
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}
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rst = {
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'Wrd': 0,
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'Corr': 0,
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'Ins': 0,
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'Del': 0,
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'Sub': 0,
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'Snt': 0,
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'Err': 0.0,
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'S.Err': 0.0,
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'wrong_words': 0,
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'wrong_sentences': 0
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}
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hyp_dict = {}
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ref_dict = {}
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with open(hyp_file, 'r') as hyp_reader:
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for line in hyp_reader:
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key = line.strip().split()[0]
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value = line.strip().split()[1:]
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if cn_postprocess:
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value = " ".join(value)
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value = value.replace(" ", "")
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if value[0] == "请":
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value = value[1:]
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value = [x for x in value]
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hyp_dict[key] = value
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with open(ref_file, 'r') as ref_reader:
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for line in ref_reader:
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key = line.strip().split()[0]
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value = line.strip().split()[1:]
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if cn_postprocess:
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value = " ".join(value)
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value = value.replace(" ", "")
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value = [x for x in value]
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ref_dict[key] = value
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cer_detail_writer = open(cer_file, 'w')
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for hyp_key in hyp_dict:
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if hyp_key in ref_dict:
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out_item = compute_wer_by_line(hyp_dict[hyp_key], ref_dict[hyp_key])
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rst['Wrd'] += out_item['nwords']
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rst['Corr'] += out_item['cor']
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rst['wrong_words'] += out_item['wrong']
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rst['Ins'] += out_item['ins']
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rst['Del'] += out_item['del']
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rst['Sub'] += out_item['sub']
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rst['Snt'] += 1
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if out_item['wrong'] > 0:
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rst['wrong_sentences'] += 1
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cer_detail_writer.write(hyp_key + print_cer_detail(out_item) + '\n')
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cer_detail_writer.write("ref:" + '\t' + " ".join(list(map(lambda x: x.lower(), ref_dict[hyp_key]))) + '\n')
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cer_detail_writer.write("hyp:" + '\t' + " ".join(list(map(lambda x: x.lower(), hyp_dict[hyp_key]))) + '\n')
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cer_detail_writer.flush()
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if rst['Wrd'] > 0:
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rst['Err'] = round(rst['wrong_words'] * 100 / rst['Wrd'], 2)
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if rst['Snt'] > 0:
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rst['S.Err'] = round(rst['wrong_sentences'] * 100 / rst['Snt'], 2)
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cer_detail_writer.write('\n')
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cer_detail_writer.write("%WER " + str(rst['Err']) + " [ " + str(rst['wrong_words']) + " / " + str(rst['Wrd']) +
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", " + str(rst['Ins']) + " ins, " + str(rst['Del']) + " del, " + str(
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rst['Sub']) + " sub ]" + '\n')
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cer_detail_writer.write(
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"%SER " + str(rst['S.Err']) + " [ " + str(rst['wrong_sentences']) + " / " + str(rst['Snt']) + " ]" + '\n')
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cer_detail_writer.write("Scored " + str(len(hyp_dict)) + " sentences, " + str(
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len(hyp_dict) - rst['Snt']) + " not present in hyp." + '\n')
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cer_detail_writer.close()
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hyp_dict = {}
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ref_dict = {}
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with open(hyp_file, 'r') as hyp_reader:
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for line in hyp_reader:
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key = line.strip().split()[0]
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value = line.strip().split()[1:]
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if cn_postprocess:
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value = value.replace(" ", "")
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value = [x for x in value]
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value = " ".join(value)
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hyp_dict[key] = value
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with open(ref_file, 'r') as ref_reader:
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for line in ref_reader:
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key = line.strip().split()[0]
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value = line.strip().split()[1:]
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if cn_postprocess:
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value = value.replace(" ", "")
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value = [x for x in value]
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value = " ".join(value)
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ref_dict[key] = value
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cer_detail_writer = open(cer_file, 'w')
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for hyp_key in hyp_dict:
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if hyp_key in ref_dict:
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out_item = compute_wer_by_line(hyp_dict[hyp_key], ref_dict[hyp_key])
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rst['Wrd'] += out_item['nwords']
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rst['Corr'] += out_item['cor']
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rst['wrong_words'] += out_item['wrong']
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rst['Ins'] += out_item['ins']
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rst['Del'] += out_item['del']
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rst['Sub'] += out_item['sub']
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rst['Snt'] += 1
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if out_item['wrong'] > 0:
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rst['wrong_sentences'] += 1
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cer_detail_writer.write(hyp_key + print_cer_detail(out_item) + '\n')
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cer_detail_writer.write("ref:" + '\t' + " ".join(list(map(lambda x: x.lower(), ref_dict[hyp_key]))) + '\n')
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cer_detail_writer.write("hyp:" + '\t' + " ".join(list(map(lambda x: x.lower(), hyp_dict[hyp_key]))) + '\n')
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cer_detail_writer.flush()
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if rst['Wrd'] > 0:
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rst['Err'] = round(rst['wrong_words'] * 100 / rst['Wrd'], 2)
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if rst['Snt'] > 0:
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rst['S.Err'] = round(rst['wrong_sentences'] * 100 / rst['Snt'], 2)
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cer_detail_writer.write('\n')
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cer_detail_writer.write("%WER " + str(rst['Err']) + " [ " + str(rst['wrong_words'])+ " / " + str(rst['Wrd']) +
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", " + str(rst['Ins']) + " ins, " + str(rst['Del']) + " del, " + str(rst['Sub']) + " sub ]" + '\n')
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cer_detail_writer.write("%SER " + str(rst['S.Err']) + " [ " + str(rst['wrong_sentences']) + " / " + str(rst['Snt']) + " ]" + '\n')
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cer_detail_writer.write("Scored " + str(len(hyp_dict)) + " sentences, " + str(len(hyp_dict) - rst['Snt']) + " not present in hyp." + '\n')
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cer_detail_writer.close()
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def compute_wer_by_line(hyp,
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ref):
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hyp = list(map(lambda x: x.lower(), hyp))
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ref = list(map(lambda x: x.lower(), ref))
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hyp = list(map(lambda x: x.lower(), hyp))
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ref = list(map(lambda x: x.lower(), ref))
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len_hyp = len(hyp)
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len_ref = len(ref)
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cost_matrix = np.zeros((len_hyp + 1, len_ref + 1), dtype=np.int16)
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ops_matrix = np.zeros((len_hyp + 1, len_ref + 1), dtype=np.int8)
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for i in range(len_hyp + 1):
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cost_matrix[i][0] = i
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for j in range(len_ref + 1):
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cost_matrix[0][j] = j
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for i in range(1, len_hyp + 1):
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for j in range(1, len_ref + 1):
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if hyp[i - 1] == ref[j - 1]:
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cost_matrix[i][j] = cost_matrix[i - 1][j - 1]
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else:
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substitution = cost_matrix[i - 1][j - 1] + 1
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insertion = cost_matrix[i - 1][j] + 1
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deletion = cost_matrix[i][j - 1] + 1
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compare_val = [substitution, insertion, deletion]
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min_val = min(compare_val)
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operation_idx = compare_val.index(min_val) + 1
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cost_matrix[i][j] = min_val
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ops_matrix[i][j] = operation_idx
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match_idx = []
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i = len_hyp
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j = len_ref
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rst = {
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'nwords': len_ref,
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'cor': 0,
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'wrong': 0,
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'ins': 0,
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'del': 0,
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'sub': 0
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}
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while i >= 0 or j >= 0:
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i_idx = max(0, i)
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j_idx = max(0, j)
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if ops_matrix[i_idx][j_idx] == 0: # correct
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if i - 1 >= 0 and j - 1 >= 0:
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match_idx.append((j - 1, i - 1))
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rst['cor'] += 1
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i -= 1
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j -= 1
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elif ops_matrix[i_idx][j_idx] == 2: # insert
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i -= 1
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rst['ins'] += 1
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elif ops_matrix[i_idx][j_idx] == 3: # delete
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j -= 1
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rst['del'] += 1
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elif ops_matrix[i_idx][j_idx] == 1: # substitute
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i -= 1
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j -= 1
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rst['sub'] += 1
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if i < 0 and j >= 0:
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rst['del'] += 1
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elif j < 0 and i >= 0:
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rst['ins'] += 1
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match_idx.reverse()
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wrong_cnt = cost_matrix[len_hyp][len_ref]
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rst['wrong'] = wrong_cnt
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return rst
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len_hyp = len(hyp)
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len_ref = len(ref)
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cost_matrix = np.zeros((len_hyp + 1, len_ref + 1), dtype=np.int16)
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ops_matrix = np.zeros((len_hyp + 1, len_ref + 1), dtype=np.int8)
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for i in range(len_hyp + 1):
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cost_matrix[i][0] = i
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for j in range(len_ref + 1):
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cost_matrix[0][j] = j
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for i in range(1, len_hyp + 1):
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for j in range(1, len_ref + 1):
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if hyp[i - 1] == ref[j - 1]:
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cost_matrix[i][j] = cost_matrix[i - 1][j - 1]
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else:
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substitution = cost_matrix[i - 1][j - 1] + 1
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insertion = cost_matrix[i - 1][j] + 1
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deletion = cost_matrix[i][j - 1] + 1
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compare_val = [substitution, insertion, deletion]
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min_val = min(compare_val)
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operation_idx = compare_val.index(min_val) + 1
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cost_matrix[i][j] = min_val
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ops_matrix[i][j] = operation_idx
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match_idx = []
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i = len_hyp
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j = len_ref
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rst = {
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'nwords': len_ref,
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'cor': 0,
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'wrong': 0,
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'ins': 0,
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'del': 0,
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'sub': 0
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}
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while i >= 0 or j >= 0:
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i_idx = max(0, i)
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j_idx = max(0, j)
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if ops_matrix[i_idx][j_idx] == 0: # correct
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if i - 1 >= 0 and j - 1 >= 0:
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match_idx.append((j - 1, i - 1))
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rst['cor'] += 1
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i -= 1
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j -= 1
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elif ops_matrix[i_idx][j_idx] == 2: # insert
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i -= 1
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rst['ins'] += 1
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elif ops_matrix[i_idx][j_idx] == 3: # delete
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j -= 1
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rst['del'] += 1
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elif ops_matrix[i_idx][j_idx] == 1: # substitute
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i -= 1
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j -= 1
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rst['sub'] += 1
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if i < 0 and j >= 0:
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rst['del'] += 1
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elif j < 0 and i >= 0:
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rst['ins'] += 1
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match_idx.reverse()
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wrong_cnt = cost_matrix[len_hyp][len_ref]
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rst['wrong'] = wrong_cnt
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return rst
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def print_cer_detail(rst):
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return ("(" + "nwords=" + str(rst['nwords']) + ",cor=" + str(rst['cor'])
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+ ",ins=" + str(rst['ins']) + ",del=" + str(rst['del']) + ",sub="
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+ str(rst['sub']) + ") corr:" + '{:.2%}'.format(rst['cor']/rst['nwords'])
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+ ",cer:" + '{:.2%}'.format(rst['wrong']/rst['nwords']))
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return ("(" + "nwords=" + str(rst['nwords']) + ",cor=" + str(rst['cor'])
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+ ",ins=" + str(rst['ins']) + ",del=" + str(rst['del']) + ",sub="
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+ str(rst['sub']) + ") corr:" + '{:.2%}'.format(rst['cor'] / rst['nwords'])
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+ ",cer:" + '{:.2%}'.format(rst['wrong'] / rst['nwords']))
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@hydra.main(config_name=None, version_base=None)
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def main_hydra(cfg: DictConfig):
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ref_file = cfg.get("ref_file", None)
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hyp_file = cfg.get("hyp_file", None)
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cer_file = cfg.get("cer_file", None)
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cn_postprocess = cfg.get("cn_postprocess", False)
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if ref_file is None or hyp_file is None or cer_file is None:
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print("usage : python -m funasr.metrics.wer ++ref_file=test.ref ++hyp_file=test.hyp ++cer_file=test.wer ++cn_postprocess=false")
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sys.exit(0)
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compute_wer(ref_file, hyp_file, cer_file, cn_postprocess)
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ref_file = cfg.get("ref_file", None)
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hyp_file = cfg.get("hyp_file", None)
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cer_file = cfg.get("cer_file", None)
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cn_postprocess = cfg.get("cn_postprocess", False)
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if ref_file is None or hyp_file is None or cer_file is None:
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print(
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"usage : python -m funasr.metrics.wer ++ref_file=test.ref ++hyp_file=test.hyp ++cer_file=test.wer ++cn_postprocess=false")
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sys.exit(0)
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compute_wer(ref_file, hyp_file, cer_file, cn_postprocess)
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if __name__ == '__main__':
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main_hydra()
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main_hydra()
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